The present invention relates to an adaptive information processing system; that is, the invention concerns a self-organizing apparatus or process for "mapping" an input into an output response, which output response may vary over time, notwithstanding the presence of the same input, as the system "learns" or is "trained." In particular, the invention relates to a new form of passive modification or self-organizing optimal mapping wherein inputs which are in different classes are separated concurrently with the passive learning of the system.
Our U.S. Pat. No. 3,950,733 issued Apr. 13, 1976 discloses an information processing system of the above-mentioned type. This system includes a module, called the Nestor.TM. adaptive module, which operates to map an input signal into an output response in accordance with a particular algorithm. When operated in a so-called "learning mode," the Nestor adaptive module modifies itself to both "learn" and forget" at desired rates. When operated in a so-called "memory mode," the module neither learns nor forgets but functions as a pure distributed memory.
When in the learning mode, the Nestor adaptive module operates with "passive modification" and can readily achieve the self-organization of a mapping:
s.sup.1 .fwdarw.r.sup.1
s.sup.2 .fwdarw.r.sup.2
s.sup.k .fwdarw.r.sup.k
from the signal space s: (s.sup.1 . . . s.sup.k) to the response space r: (r.sup.1 . . . r.sup.k) if s.sup.1 . . . s.sup.k are orthogonal. If s.sup.1 . . . s.sup.k are not orthogonal, passive modification can also achieve recognition as well as class formation. However, some additional new feature is required for class separation.